Archive for February, 2015

The Brookings Institution just published a paper outlining the importance of our advanced industries (AI), and a call to do more to support its growth. To be classified as advanced industries must spend more than $450 per worker on R&D, putting them in the 80th percentile, and the share of workers whose jobs demand a high degree of STEM (Science, Technology, Engineering and Math) knowledge must exceed the national average of 21%. Overall, industries so classed constitute our tech sector at its broadest: most manufacturing operations including aerospace, automotive, navigational instruments, medical equipment and supplies; energy including electric power, mining and extraction; and services, including architecture and engineering, data processing, satellite communication and scientific research.

Between 1980 and 2013 such industries grew 30% faster than the rest of the economy, or 5.4% annually, but employment levels held basically steady, largely because of productivity advances. Since the Great Recession both activity and employment have been on the rise, the sector adding one million direct jobs between 2010 and 2013, with employment and output rates 1.9 and 2.3 times faster than the nation as a whole. And AI employment has a high multiplier: those 1 million direct jobs likely generated another 2.2 million outside the industry itself, which compares to about 6 million total jobs created nationally over the same stretch. Advanced services were responsible for 65% of the total AI jobs, with computer design by itself up 250,000. Industries building transportation equipment have been adding jobs, finally, after decades of losses. A lot of attention has been focused on contributions to national payroll gains made by AI subsector gas and oil extraction since the recession.

A boost? Certainly, but dwarfed by the mothership.

Each worker in the sector generates about $210,000 in value added, in comparison to the $101,000 average overall, which helps offset the sharp increase in wages. In 2013 the average AI worker earned $90,000 annually, close to twice the overall average. Between 1975 and 2013 inflation-adjusted AI wages were up 63%, compared with 17% outside the sector. Total AI employment was about 12.3 million in 2013, about 9% of total overall employment, with another 27 million jobs riding AI's coattails. Together with the directly employed, that’s about one-fourth of US employment. Surprisingly, about half of the workers in the sector hold less than a bachelor’s degree, and Brookings ranks it as an accessible field. And one where more workers are needed.

Computer systems design owns the largest share of total AI employment, 13.8%, followed by architecture and engineering, 11.0% and management and technological consulting, 9.6%. Between 2010 and 2013 fastest rates of employment growth took place in information services, 10%; railroad rolling stock, 8.4%; automotive, 8.1%, and gas and oil extraction 7.6%.

Advanced industries tend to thrive in urban areas: San Jose is our most advanced hub, with 30% of the workforce laboring in the sector, followed by Seattle, 16%, Wichita, 15.5%, Detroit, 14.8%, and San Francisco, 14%. San Jose, Detroit and Seattle have the broadest array of advanced industry. (We’ll be presenting more data on this in coming months.)

We are losing international share, and there are a host of serious problems we like to nag about, but even in its somewhat weakened state our AI sector a powerful thing. And if we’re worried about productivity, as we should be, it’s a great place to start.

Lately we’ve been seeing the argument made that the labor market is tighter than it looks. The argument goes like this: while the decline in the unemployment rate may have been boosted by labor force withdrawal, many of the dropouts will never work again, so it’s wrong to adjust the official jobless rate, either statistically or mentally, to compensate for depressed participation rates. So January’s 6.6% unemployment rate, 0.1 point above the Fed’s long-standing trigger, is getting close to “full employment,” and it would be prudent to start thinking about raising the fed funds rate sooner than most market participants expect. Is there anything to this?

We think not. For one, a 6.6% rate is about two-thirds of a standard deviation above the 1948–2007 average of 5.6%, which is not trivial. It’s even further above, in absolute terms, its 2002–2007 average of 5.3%, an expansion that was far from robust. It may be close to the Congressional Budget Office’s estimate of the “natural” rate of 6.0%, but as we showed last month, there’s nothing very scientific about these estimates; just six years ago, the CBO projected that the natural rate would be 4.8% right now.

A more subtle version of the argument looks at sectoral unemployment rates and finds some getting awfully close to full employment. We have a hard time seeing that. Graphed at right are unemployment rates by major sector compared to their 2000–2007 averages. In only one sector—manufacturing—is the January 2014 unemployment rate close to its average, though it’s 0.1 point above. Next closest is finance, 0.8 point above. The others are 1–2 percentage points above their average. A nice theory, but it just doesn't hold water.

Relatedly, some analysts are detecting wage pressures under a placid overall average—a 1.9% gain for the year ending in January. One argued that weakness in financial sector pay is dragging down the average. But if you do a weighted average of hourly wage growth excluding that sector, you still get 1.9%. Most major sectors, accounting for 72% of total private employment, exhibit wage growth below their 2007 average. In fact, wage growth is slower than it was a year ago—and that’s true of sectors accounting for 68% of private employment. It’s hard to see any tightness here either.

quit rates

Another place to look for signs of labor market tightness is in the quit rate. If workers perceive jobs as easy to get, they’re more likely to quit on their own. And, short of that, they’re more likely to demand raises from employers eager to keep them. But currently the quit rate is low by historical standards.

The BLS started publishing the quit rate in 2000. Since the quit rate tracks the number of those unemployed 5 weeks or less very closely, we used that series to estimate the quit rate going back to 1967. (Where the two series overlap, the fit is very tight—an r2 of 0.93.) December’s 1.7% rate is well below the full series’ 2.1% average. It’s also well below levels seen close to previous business cycle peaks, like 1979, 1989, 1999, and 2007.

The quit rate moves generally in line with the unemployment rate. You can “predict” the unemployment rate with decent accuracy with the quit rate, in fact. But as the graph on the bottom of this page shows, the unemployment rate associated with the December 2013 quit rate is a full point above its actual level. Or, putting it more bluntly, workers are acting as if December’s unemployment rate were 7.7%, not the 6.7% it actually was. If the job market were tighter than it looks, we’d expect a much higher quit rate.